<OL> <LI> Determine the impact of the quality defects of market cows and bulls on economic value. <LI> Determine the impact of post-harvest interventions on the quality and safety attributes of pork and beef products. Objective one expected to be completed by the end of year 3; objective two by the end of year 5.
NON-TECHNICAL SUMMARY: <BR> Pre-Harvest: The National Cattlemen's Beef Association (NCBA) has worked for more than 15 years to identify quality challenges in beef carcasses. Starting with the initial National Beef Quality Audit in 1991 (Smith et al., 1992), researchers identified the relevance of quality challenges in the beef industry and documented the leading concerns to be (1) excessive external fat, (2) low overall uniformity of beef, (3) low overall uniformity of live cattle, (4) excessive seam fat, (5) price too high, (6) inadequate understanding of the value of closer-trimmed beef, (7) low overall cutability, (8) low overall palatability, (9) too frequent hide problems, and (10) too high incidence of injection-site blemishes. <BR> <BR> Beginning in 1990, researchers discovered that pre-harvest management practices were impacting beef quality. As such, in recent years, the beef industry has focused on improving the quality and consistency of beef products offered to consumers and there has been further emphasis placed on improving the quality characteristics of steer and heifer carcasses (Smith et al., 2001). This emphasis, however, has not been placed on market cows and bulls at the same level of emphasis by producers. <BR> <BR> Post-Harvest: Several outbreaks of food borne illness caused by meat products containing Escherichia coli 0157:H7 have occurred in this country in recent years. This has led to much speculation as how to control the pathogen load in/on meat products. Such outbreaks point to the potential hazards associated with the consumption of under-cooked products. A better understanding of surface treatments to control pathogens would provide helpful information relative to development of post harvest interventions. Researchers have documented that feeding lactobacillus based direct fed microbials to cattle will reduce E. coli O157:H7 prevalence in cattle (Stephens et al., 2007a, 2007b); however, the question remains to see if a post-harvest application of lactobacillus is a potential intervention step. Duffy et al. (2001) has documented that nearly 10% of pork product in retail settings are contaminated with Salmonella spp. Duffy et al. (2001) also documented that pork products exposed to the most handling and processing appeared to be in the poorest microbiological condition. Zhang et al. (2008) has conducted work evaluating the antimicrobial activity of spice extracts against pathogenic and spoilage bacteria in pork, documenting that a mix of rosemary and liquorice extracts serves as a natural preservative in fresh pork. However, limited research on post-harvest applications of antimicrobial sprays has been published relative to the pork industry to date.
APPROACH: <BR> Experiment 1 (Objective 1) To quantify the incidence of quality defects in beef and dairy market cows and bulls, data will be collected at major livestock auction markets with regular weekly sales. The presence of specific BQA-related defects will also be recorded, including brand presence and size/number, horn presence and length, ocular neoplasia, injection site knot presence and location, abscess or body sore presence and location, and presence of foot abnormalities, leg bands, bottle teats, mastitis evidence, surgery evidence, retained placenta, and prolapsed rectum or vagina/uterus. Data will only be collected on bulls and cows intended for immediate harvest. Statistical Analysis: The frequency of observed factors (by sex and type) will be determined using PROC SURVEYFREQ procedures of SAS. In addition to documenting the incidence rates for BQA-related defects, a model and framework will be derived to determine the positive and negative price impacts resulting from observed BQA-related factors. <BR> <BR> Experiment 2 (Objective 2) Three separate studies, two with pathogen-inoculated product and two with noninoculated product will be conducted to determine the impacts on quality and safety of steaks, chops and ground beef and pork when using a lactobacillus surface treatment. <BR> <BR> Study 1: Inoculated samples Part 1: Fat samples will be inoculated with a cell suspension of E. coli 0157:H7 and/or Salmonella enteritidis. Control samples will be treated in a like manner using sterile buffer of the same composition as for the bacterial cell suspension. After inoculation, samples will be surface treated with lactobacillus isolates shown to have inhibitory effects on Salmonella and E. coli spp. Following the surface treatment, product will be packed and placed in simulated retail display. Daily for one week, samples will be taken from the retail case to determine the microbial load of each sample. <BR> <BR> Study 2: Inoculated samples Part 2: Product samples will be inoculated with a cell suspension of E. coli 0157:H7 and/or Salmonella enteritidis. Control samples will be treated in a like manner using sterile buffer of the same composition as for the bacterial cell suspension. After inoculation, samples will be surface treated with lactobacillus isolates shown to have inhibitory effects on Salmonella and E. coli spp. Daily for one week, samples will be taken from the retail case to determine the microbial load of each sample. The package slated for display the entire week will be color scored twice daily. <BR> <BR> Study 3: Noninoculated samples: Product samples will be surface treated as above, packaged and placed in retail display. Daily for one week, samples will be taken from the retail case to determine the microbial load and to determine sensory attributes of the product. In addition, as stated above, the package slated for display the entire week will be color scored twice daily. <BR> <BR> Statistical Analysis: Data will be analyzed using the PROC MIXED procedure of SAS to determine LS means for microbial load; data will be transformed using a log10 transformation prior to analysis. Least squares means will be calculated and reported.